Principal Supercomputing Operations Software Engineer

Microsoft’s Azure AI and High Performance Computing organization builds and operates large-scale supercomputing environments for AI training, scientific computing, and simulations. The Principal Supercomputing Operations Software Engineer owns interconnect fabric operations, leads complex incidents, and drives reliability, automation, diagnostics, and operational standards across these environments.

Responsibilities:

• Serve as the technical authority and DRI for InfiniBand and GPU interconnect fabric operations across large scale AI supercomputing environments, ensuring sustained GPU availability, training stability, and SLA compliance
• Lead and orchestrate complex, high severity fabric incidents end to end, including detection, triage, mitigation, recovery, and root cause analysis, making high impact decisions under ambiguity
• Perform deep, multi layer systems debugging across InfiniBand, Subnet Manager, GPU interconnect, PCIe, GPUs, firmware, drivers, and OS layers to identify true root causes at fleet scale
• Drive operational excellence and systemic prevention by identifying recurring failure patterns, defining reliability models and failure domains, and authoring authoritative TSGs, playbooks, and escalation frameworks adopted across teams
• Architect and drive automation, telemetry, diagnostics, and tooling that materially improve detection, observability, debuggability, and mean time to mitigation, raising the operational bar for interconnect fabrics across the platform

Requirements:

• Bachelor's Degree in Computer Science or related technical field AND 6+ years technical engineering experience with coding in languages including, but not limited to, C, C++, C#, Java, JavaScript, or Python

• OR equivalent experience

• Ability to meet Microsoft, customer and/or government security screening requirements are required for this role
• 6+ years of experience operating large‑scale distributed systems, high‑performance computing (HPC), or artificial intelligence (AI) infrastructure in production environments
• Demonstrated ownership of mission‑critical production infrastructure with direct impact on service availability, GPU workloads, and customer SLAs
• Hands‑on experience operating and debugging interconnect fabrics supporting large‑scale compute workloads
• Strong Linux systems knowledge with experience debugging low‑level infrastructure issues across operating systems, drivers, and services
• Proven ability to reason across hardware, firmware, drivers, and software stacks to diagnose and resolve complex production issues
• Bachelor's Degree in Computer Science

• OR related technical field AND 10+ years technical engineering experience with coding in languages including, but not limited to, C, C++, C#, Java, JavaScript, OR Python
• OR Master's Degree in Computer Science or related technical field AND 8+ years technical engineering experience with coding in languages including, but not limited to, C, C++, C#, Java, JavaScript, or Python
• OR equivalent experience